![]() ![]() This is the code I wrote: import pandas as pd import numpy as np import pandas. The * will cause the ADF to be extremely slow.Excel generate sql insert. MySQL view, make sure the view's select statement has included explicit column names instead of select *. pipelineNameĭatabase view must have explicit column names To log the child pipeline's failure, it can retrieve the child pipeline's name from activity ( 'Execute Pipeline' ). However, we can create a parent pipeline to run the pipeline (Execute pipeline task) and capture the whole child pipeline's failure from there. In Azure, there is no pipeline level 'try-catch' or failure capture, so it needs to set up the failure capture for every component. (2) deleting old data is more efficient as it can just truncate the old partitions, while deleting old rows from a table involves too much logging and is very slow. (a) querying data is more efficient by limiting to only one partition MySQL, as the size of the table can be quite big after a period of time, we can partition the table by e.g. If the 'append' option is available for writing to a file, then it may just append all small result sets into a single file. If the pipeline generates too many small files due to many small queries in a loop, we may load all small result sets into a database and then export all into a single file at the end. If too big, it may need to divide the load window into smaller windows. If the load window is small enough, just load from where it was up to in the last run until now. But if the timestamp is the actual insert datetime, then there won't be any row with insert timestamp earlier than now(). The reason is: A data row with timestamp at 12:00 may not be inserted to the system until 12:01 for example. ![]() When logging the load window, the end time should be rewritten with the max data timestamp if the timestamp is not the insert datetime. It checks the execution log (for last load window end time as the start time) and use now() as the window end time. It can be done by SQL script on the database side (mysql or sql server) and exposed to Azure through a database view. Then an 'If Condition' can direct the logic flow based on the flag file exists or not. In the pipeline, the 'Get Metadata' task can be used for checking if a flag file exists or not. There is no task for creating a file either, so it needs to set up a Copy task to copy a static file to a flag file using e.g. If using non SQL server, the script task is not available in Azure, then one way is to create a file in the data lake to indicate the pipeline is running. This requires a 'Script' task to create & update the flag accordingly. One approach is to set a flag within the execution log database table to indicate an active instance is running. There seems to be a work around tho.Īzure Data factory doesn't skip pipeline when an existing instance is running. However, dataflow source doesn't natively support parameterized source yet. Then when using the dataset in a pipeline, it will ask for the parameter, then it can map a variable to the parameter will work.ĭataset can not use a variable dynamically in the path, but a dataset can use a parameter ![]() Note, if the file name contains colon character : which can be part of a time string, then dataflow doesn't workĪnd raise "Relative Path in Absolute URI error" but replacing the colon : to e.g. The folder path should be the subfolders, e.g. In the path, the container is pre populated ![]() The source of 'copy data' is set to use wildcard file path The datalake dataset points to the subfolder, e.g. can point / query different things dynamically.ĬonvertFromUtc ( utcNow (), 'AUS Eastern Standard Time', 'yyyy-MM-dd' 'AUS Eastern Standard Time', 'yyyy-MM-dd HH:mm:ss.ffffff')Īzure Data factory does NOT support 'logical or' when combining flows from two activities.Īzure Data Factory does NOT allow running ForEach loop within an IF Condition, but can run IF condition within a ForEach Loop.Ĭan do upsert with copy task, maybe only sql targets? The dynamic content with source query / directory path etc. ![]()
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